Fernando Miguel Gamboa Antiñolo
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Research Interests
Fernando Miguel Gamboa Antiñolo has a total of 195 co-authors. Here are the top co-authors by number of shared publications:
J. Vega Sánchez
Servicio de Medicina Interna. Unidad de Continuidad Asistencial. Hospital El Tomillar. Sevilla
3 shared publications- Martin Tygel
Universidade Estadual de Campinas, Campinas, SP
3 shared publications R. López Alonso
Servicio de Medicina Interna. Unidad de Continuidad Asistencial. Hospital El Tomillar. Sevilla
3 shared publicationsE. Gómez Camacho
2 shared publicationsE. de Villar Conde
2 shared publicationsF García-Bragado
2 shared publications
Latest Publications
- 19 December 2023
- Published by Elsevier in Revista Clínica Española
- Vol. 223, S136-S138
515 - INTERACCIONES FARMACOLÓGICAS EN LA ATENCIÓN A PACIENTES PLURIPATÓLOGICOS
- 19 December 2023
- Published by Elsevier in Revista Clínica Española
- Vol. 223, S136-S138
515 - INTERACCIONES FARMACOLÓGICAS EN LA ATENCIÓN A PACIENTES PLURIPATÓLOGICOS
- 19 December 2023
- Published by Elsevier in Revista Clínica Española
- Vol. 223, S480-S481
519 - LA MUSICOTERAPIA COMO TRATAMIENTO NO FARMACOLÓGICO EN LA ENFERMEDAD DE ALZHEIMER
- 19 December 2023
- Published by Elsevier in Revista Clínica Española
- Vol. 223, S480-S481
519 - LA MUSICOTERAPIA COMO TRATAMIENTO NO FARMACOLÓGICO EN LA ENFERMEDAD DE ALZHEIMER
- Open Access
- 22 February 2023
- Published by Springer Nature in Internal and Emergency Medicine
- Vol. 18 (5) , 1259-1261
Diabetic foot ulcers: a growing global health emergency in the COVID-19 era
- 22 February 2023
- Published by Springer Nature in Internal and Emergency Medicine
- Vol. 18 (5) , 1259-1261
Open AccessDiabetic foot ulcers: a growing global health emergency in the COVID-19 era
- 25 August 2022
- Published by Elsevier in Medicina Clinica
- Vol. 159 (10) , e65-E65
Modelos de predicción de riesgo de morbimortalidad en sepsis
- 25 August 2022
- Published by Elsevier in Medicina Clinica
- Vol. 159 (10) , e65-E65
Modelos de predicción de riesgo de morbimortalidad en sepsis
- Open Access
- 1 July 2021
- Published by Elsevier in Gaceta Sanitaria
- Vol. 35 (4) , 358-360
La objeción de conciencia de los profesionales sanitarios
- 1 July 2021
- Published by Elsevier in Gaceta Sanitaria
- Vol. 35 (4) , 358-360
Open AccessLa objeción de conciencia de los profesionales sanitarios
- 13 April 2021
- Published by Springer Nature in Internal and Emergency Medicine
- Vol. 16 (4) , 1027-1030
Prognostic tools for elderly patients with sepsis: in search of new predictive models
As a tool to support clinical decision-making, Mortality Prediction Models (MPM) can help clinicians stratify and predict patient risk. There are numerous scoring systems for patients with sepsis that predict sepsis-related mortality and the severity of sepsis. But there are currently no MPMs for adults with sepsis who meet the criteria of "good." Clinicians are unlikely to use complex MPMs that require extensive or expensive data collection to impede workflow. Machine learning applied to minimal medical records of patients diagnosed with sepsis can be a useful tool. Progress is needed in the development and validation of clinical decision support tools that can assist in patient risk stratification, prognosis, discussion of patient outcomes, and shared decision making.
- 13 April 2021
- Published by Springer Nature in Internal and Emergency Medicine
- Vol. 16 (4) , 1027-1030
Prognostic tools for elderly patients with sepsis: in search of new predictive models
As a tool to support clinical decision-making, Mortality Prediction Models (MPM) can help clinicians stratify and predict patient risk. There are numerous scoring systems for patients with sepsis that predict sepsis-related mortality and the severity of sepsis. But there are currently no MPMs for adults with sepsis who meet the criteria of "good." Clinicians are unlikely to use complex MPMs that require extensive or expensive data collection to impede workflow. Machine learning applied to minimal medical records of patients diagnosed with sepsis can be a useful tool. Progress is needed in the development and validation of clinical decision support tools that can assist in patient risk stratification, prognosis, discussion of patient outcomes, and shared decision making.
- 1 March 2021
- Published by Elsevier in Revista Clínica Española (English Edition)
- Vol. 221 (3) , 184-185
The COVID-19 era: Ethics in times of crisis
- 1 March 2021
- Published by Elsevier in Revista Clínica Española (English Edition)
- Vol. 221 (3) , 184-185
The COVID-19 era: Ethics in times of crisis
- Open Access
- 1 March 2021
- Published by Elsevier in Gaceta Sanitaria
- Vol. 35 (2) , 208
Pandemic, public policy and ethics
- 1 March 2021
- Published by Elsevier in Gaceta Sanitaria
- Vol. 35 (2) , 208
Open AccessPandemic, public policy and ethics
- 1 September 2020
- Published by Springer Nature in Internal and Emergency Medicine
- Vol. 15 (6) , 925-927
Organizational determinants of hospital stay: increasing hospital efficiency
- 1 September 2020
- Published by Springer Nature in Internal and Emergency Medicine
- Vol. 15 (6) , 925-927
Organizational determinants of hospital stay: increasing hospital efficiency
- 1 April 2020
- Published by Springer Nature in Internal and Emergency Medicine
- Vol. 15 (4) , 557-558
Comorbidity, clinical complexity and palliative care
- 1 April 2020
- Published by Springer Nature in Internal and Emergency Medicine
- Vol. 15 (4) , 557-558
Comorbidity, clinical complexity and palliative care